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Hymba 1.5B Base by nvidia

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  Arxiv:2411.13676   Autotrain compatible   Conversational   Custom code   Hymba   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/nvidia/Hymba-1.5B-Base 

Hymba 1.5B Base Benchmarks

MMLU Pro: 10.25
GPQA: 0.78
MUSR: 5.18
BBH: 7.69
IFEval: 22.95 vs 88 (so35)-73.9%
MATH Lvl 5: 1.36
LLME Score: 0.2369
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Hymba 1.5B Base (nvidia/Hymba-1.5B-Base)
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Hymba 1.5B Base Parameters and Internals

Model Type 
text-to-text
Use Cases 
Limitations:
The model may amplify biases and return toxic responses., The model may generate inaccurate or socially undesirable text., The model is susceptible to jailbreak attacks.
Additional Notes 
Meta tokens, a set of learnable tokens, are prepended to every prompt to improve efficacy. The model shares KV cache between 2 layers and between heads in a single layer. 90% of attention layers are sliding window attention.
Training Details 
Training Time:
September 1, 2024 - November 10, 2024
Model Architecture:
Hymba-1.5B-Base has a model embedding size of 1600, 25 attention heads, and an MLP intermediate dimension of 5504, with 32 layers in total, 16 SSM states, 3 full attention layers, the rest are sliding window attention. Each attention layer in Hymba has a hybrid combination of standard attention heads and Mamba heads in parallel. Additionally, it uses Grouped-Query Attention (GQA) and Rotary Position Embeddings (RoPE).
Responsible Ai Considerations 
Accountability:
Developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.
Mitigation Strategies:
Strong output validation controls are recommended to handle security and safety risks.
Input Output 
Performance Tips:
The batch size needs to be 1 during generation due to current implementation limitations.
LLM NameHymba 1.5B Base
Repository 🤗https://huggingface.co/nvidia/Hymba-1.5B-Base 
Model Size1.5b
Required VRAM3 GB
Updated2025-09-23
Maintainernvidia
Model Typehymba
Model Files  3.0 GB
Model ArchitectureHymbaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.44.0
Tokenizer ClassLlamaTokenizer
Padding Token[PAD]
Vocabulary Size32001
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than nvidia/Hymba-1.5B-Base.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Release v20241124
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